Quantitative trait loci for morphometric and mineral composition traits of the tibia bone in a broiler × layer cross

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Abstract

Many economic losses occur in the poultry industry due to leg fragility. Knowing the genomic regions that influence traits associated with the growth and composition of the leg’s bone can help to improve the selection process leading to increased leg resistance to fracture. The present study aimed to map quantitative trait loci (QTL) for mineral composition and morphometric traits of the tibia in 478 animals from an F2 broiler × layer cross. The measurement of weight, length and width of Tibia was carried out at 42 days of age. Ash, dry matter, levels of calcium (Ca), phosphorus (P), magnesium (Mg), Zinc (Zn) and Calcium:Phosphorus (Ca:P) ratio were also recorded. The population was genotyped for 128 microsatellite markers and one single nucleotide polymorphism, covering 2630 cM of the chicken genome. A likelihood ratio test was performed to find QTLs. Additive and dominance effects of the QTLs were included in the model. In the chromosomes 2 (GGA2), 6 (GGA6), 8 (GGA8), 24 (GGA24) and 26 (GGA26) some suggestive QTLs ( P<0.00276) were mapped for tibia weight (GGA2 and GGA26), ash percentage (GGA2 and GGA6), dry matter percentage (GGA2), Ca (GGA8 and GGA24) and Ca:P ratio (GGA8), many of which are close to genes already identified as good candidates for those traits. The suggestive QTL on GGA2 has a pleiotropic effect on ash percentage, dry matter and bone weight, whereas in the GGA8 there seems to be two QTLs, one for Ca and another for Ca:P ratio. Thus, this study identified at least five genomic regions, in different chromosomes, that can be targeted for further research to identify potential mutations influencing the development and composition of leg bones in Gallus gallus.

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A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

C S Haley, S Knott (1992)

The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.

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The role of nutrients in bone health, from A to Z.

Cristina Palacios (2005)

Osteoporosis is a major public health problem, affecting millions of individuals. Dietary intake is an important modifiable factor for bone health. Inadequate intake of nutrients important to bone increases the risk for bone loss and subsequent osteoporosis. The process of bone formation requires an adequate and constant supply of nutrients, such as calcium, protein, magnesium, phosphorus, vitamin D, potassium, and fluoride. However, there are several other vitamins and minerals needed for metabolic processes related to bone, including manganese, copper, boron, iron, zinc, vitamin A, vitamin K, vitamin C, and the B vitamins. Although the recommended levels of nutrients traditionally related to bone were aimed to promote bone mass and strength, the recommended levels of the other nutrients that also influence bone were set on different parameters, and may not be optimal for bone health, in view of recent epidemiological studies and clinical trials.